Personne

Adrien Christophe Doerig

Cette personne n’est plus à l’EPFL

Publications associées (34)

Why computational complexity may set impenetrable barriers for epistemic reductionism

Michael Herzog, Christian Sachse, Adrien Christophe Doerig

According to physicalism, everything is physical or metaphysically connected to the physical. If physicalism were true, it seems that we should - in principle - be able to reduce the descriptions and explanations of special sciences to physical ones, for e ...

Dordrecht2023

Fixing the problems of deep neural networks will require better training data and learning algorithms

Martin Schrimpf, Adrien Christophe Doerig, Matthias Bethge, Jianghao Liu, Kuntal Ghosh

Bowers et al. argue that deep neural networks (DNNs) are poor models of biological vision because they often learn to rival human accuracy by relying on strategies that differ markedly from those of humans. We show that this problem is worsening as DNNs ar ...

Cambridge2023

First-person experience cannot rescue causal structure theories from the unfolding argument

Michael Herzog, Adrien Christophe Doerig, Aaron Schurger

We recently put forward an argument, the Unfolding Argument (UA), that integrated information theory (IIT) and other causal structure theories are either already falsified or unfalsifiable, which provoked significant criticism. It seems that we and the cri ...

Elsevier2022

Global information processing in feedforward deep networks

Michael Herzog, Ben Henrik Lönnqvist, Adrien Christophe Doerig, Alban Bornet

While deep neural networks are state-of-the-art models of many parts of the human visual system, here we show that they fail to process global information in a humanlike manner. First, using visual crowding as a probe into global visual information process ...

2022

How crowding challenges (feedforward) convolutional neural networks

Michael Herzog, Ben Henrik Lönnqvist, Gregory Francis, Adrien Christophe Doerig, Alban Bornet, Lynn Schmittwilken

Are (feedforward) convolutional neural networks (CNNs) good models for the human visual system? Here, we used visual crowding as a well-controlled psychophysical test to probe CNNs. Visual crowding is a ubiquitous breakdown of object recognition in the hum ...

2021

A new empirical challenge for local theories of consciousness

Adrien Christophe Doerig

Local theories of consciousness state that one is conscious of a feature if it is adequately represented and processed in sensory brain areas, given some background conditions. We challenge the core prediction of local theories based on long-lasting postdi ...

WILEY2021

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In visual crowding, the perception of a target deteriorates in the presence of nearby flankers. Traditionally, target-flanker interactions have been considered as local, mostly deleterious, low-level, and feature specific, occurring when information is poo ...

ASSOC RESEARCH VISION OPHTHALMOLOGY INC2021

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In crowding, perception of a target deteriorates in the presence of nearby flankers. Traditionally, it is thought that visual crowding obeys Bouma's law, i.e., all elements within a certain distance interfere with the target, and that adding more elements ...

PUBLIC LIBRARY SCIENCE2021

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Classically, visual processing is described as a cascade of local feedforward computations. Feedforward Convolutional Neural Networks (ffCNNs) have shown how powerful such models can be. However, using visual crowding as a well-controlled challenge, we pre ...

2020

Classically, vision is seen as a cascade of local, feedforward computations. This framework has been tremendously successful, inspiring a wide range of ground-breaking findings in neuroscience and computer vision. Recently, feedforward Convolutional Neural ...

EPFL2020

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